The rapid development of digital financial platforms has transformed the way retail investors obtain information, select investments, and execute trades. Social trading networks represent an important development within this transformation because they combine conventional online trading with social-network characteristics such as profiles, rankings, follower counts, performance statistics, comments, popularity indicators, and automated trade replication. Copy trading, one of the defining features of social trading, enables investors to automatically replicate the transactions of another trader. Although this mechanism can reduce information and skill barriers for inexperienced investors, it may simultaneously intensify investor imitation and collective decision-making. This research paper examines the copy trading herd effect through the theoretical lens of behavioral finance. It investigates how social signals, popularity, trust, past performance, visibility, reputation, risk perceptions, and platform design can influence investors' decisions to follow and copy other traders. The paper integrates traditional theories of financial herding with behavioral concepts including information cascades, social proof, overconfidence, attention, confirmation bias, reputation effects, and bounded rationality. It further distinguishes between rational information-based imitation and irrational or socially motivated herding. The study adopts a conceptual and literature-based research methodology. Existing theoretical and empirical research on herding, individual investor behavior, social trading, copy trading, social networks, and digital investment platforms is synthesized to develop an integrated framework. Evidence from experimental and platform-based studies indicates that social signals can significantly influence trader selection and that the availability of copy trading can increase risk taking. Research also suggests that highly active behavior may be associated with poorer returns and that popularity does not necessarily represent persistent investment skill. The paper concludes that social trading networks create a distinctive behavioral environment in which investment decisions can become increasingly interconnected. The copy-trading herd effect may improve access to investment information and facilitate learning, but it can also generate excessive risk-taking, concentration, delayed reactions, and synchronized trading. The paper proposes implications for investors, financial intermediaries, social-trading platforms, regulators, and financial educators. Keywords: Social trading, copy trading, herd behavior, behavioral finance, investor imitation, social networks, retail investors, financial technology, social influence, investment risk